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Consenso de expertos sobre la competencia en inteligencia artificial para educadores médicos (Edición 2025)

Hui Pan1, Meng-Chun Gong2, Jing-Hui Lu2

  • 1Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.

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Resumen

Este consenso introduce un marco de competencia en IA para educadores médicos para navegar la inteligencia artificial generativa (IA) en la educación. Describe las competencias básicas para la integración efectiva de la IA y el desarrollo profesional en la formación médica.

Palabras clave:
competencia en inteligencia artificialmarco de competenciasdesarrollo del educadorconsenso de expertoseducación médica

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Área de la Ciencia:

  • Educación Médica
  • Inteligencia Artificial
  • Salud Digital

Sus antecedentes:

  • La inteligencia artificial generativa (IA) presenta desafíos y oportunidades significativos en la educación médica.
  • Existe la necesidad de un marco estructurado para guiar a los educadores médicos en el desarrollo de la competencia en IA.

Objetivo del estudio:

  • Proponer un marco integral de competencia en IA para educadores médicos (CAIP-ME).
  • Establecer ítems de competencia centrales y estándares de evaluación para la competencia en IA en educadores médicos.

Principales métodos:

  • Revisión sistemática de la literatura.
  • Construcción preliminar del marco.
  • Múltiples rondas de pre-estudio de expertos.
  • Método Delphi estructurado con 60 expertos interdisciplinarios.

Principales resultados:

  • Se desarrolló un marco con cinco dimensiones centrales y 25 ítems de competencia específicos.
  • Las competencias se categorizan en 11 ítems fundamentales y 14 ítems de desarrollo.
  • Cada ítem incluye definiciones, manifestaciones conductuales e indicadores de evaluación.

Conclusiones:

  • El marco CAIP-ME proporciona una base científica para el desarrollo profesional de los educadores médicos.
  • Apoya la creación de facultades y sirve como referencia para la transformación digital en la educación médica.
  • Este marco tiene como objetivo mejorar la competencia en IA entre los educadores médicos para mejorar la enseñanza y el aprendizaje.